The present embodiments relate to tissue characterization in medical imaging.
Magnetic resonance images are widely used in medical diagnosis and therapy. For example, magnetic resonance is used for breast tumor diagnosis following the guidelines of the Breast Imaging-Reporting and Data System (BIRADS), which are based on clinically descriptive tags like mass (shape, margin, mass enhancement), symmetry or asymmetry, non-mess-like enhancement in an area that is not a mass (distribution modifiers, internal enhancement), kinetic curve assessment, and other findings. Similarly for prostate, the Prostate Imaging and Reporting and Data System (PIRADS) specifies the clinically descriptive tags for special prostate regions, such as peripheral zone, central zone, and transition zone. For liver tissue characterization, fibrosis staging is possible based on reading of the magnetic resonance images. Similar approaches are used in other imaging modalities, such as ultrasound, computed tomography, positron emission tomography, or single photon emission computed tomography.
To assess therapy, multimodal magnetic resonance scans are acquired before and after therapy. A simple morphological (e.g., size-based) scoring is commonly performed in tumor treatment assessment, such as the Response Evaluation Criteria in Solid Tumors (RECIST) criteria. The assessment of treatment response is critical in determining the course of continuing treatment since chemotherapy drugs may have adverse effects on the patient. In basic clinical settings, treatment assessment is done morphologically with tumor size. Due to this simple approach, it can take longer to determine if a treatment is succeeding.
The decision to stop therapy may occur earlier by employing functional magnetic resonance information than with the RECIST criteria. For example, treatment effectiveness may be determined earlier by using image-based functional measurements, such as intensity based histograms of the functional measures. These histogram-based intensity values are manually analyzed in clinical practice and may not necessarily capture subtleties related to image texture and local dissimilarity that may better represent cell density, vasculature, necrosis, or hemorrhage characteristics important to clinical diagnosis.